In this article, you’ll gain insight into what enterprise federated search is, what benefits your organization can expect to achieve rapidly, how to implement enterprise search in a phased approach for maximum value, and what other researchers and leaders in your industry about how and why to implement an enterprise search capability.
Federated search allows multiple data sources to be searched simultaneously and seamlessly using a single search interface. This single interface presents a consolidated view of results from various queries internally and even to multiple external search engines.
Search engines are often equated to “federated search,” but a search engine is just software. Federated Search includes a search engine but is much broader.
Organizations both public and private invest in federated search for many reasons. The primary reasons, in ranked order from surveys, are:
- Efficiency. Time savings in responding to urgent regulatory requests and queries. Less than 20% of organizations believe they are excellent at decision-making, and most agree that speed is a bigger challenge than quality.
- Speed. Decision-makers require quick access to a variety of data in real time. The ability to scan the organization’s knowledge base and various apps gives them the power to make timely decisions.
- Costly delays. Without an enterprise search solution, decision-making requires a team of employees to collect and organize relevant data. The delay can affect the efficiency of a time-sensitive decision.
- Fewer bottlenecks. Newer employees require training and experience. They can’t achieve competence without access to the right information. And often there are precious few employees or contractors with expert-level knowledge.
- Ease of Use Drives. Lowers barriers to usage with a simple, single-user interface compared to multiple systems for querying, and various formats of output to then be consolidated.
- Training Time Reduction. Significant reduction in training time, and training materials development
- Storage and compute cost reduction. Reduction in storage costs and replication time and costs, by eliminating the need for duplicating data
- Better data access reporting. Data access rights, tracking, and reporting are increasingly more complicated as legislation enhances data protection. Many companies struggle with the problem of employees unintentionally revealing confidential information. From employee details to trade secrets, data from company documents can be sensitive.
- Data Access Mistakes. Accidental access to classified or confidential information happens in every organization. Often, it is as minor as mistakenly getting access at a folder level instead of a document level. With an enterprise search solution, you can control how employees access the information to make sure data isn’t accessed by individuals who should not have access.
Traditional approaches to someone searching for an answer involve many steps, with many challenges and inefficiencies. The table below summarizes this.
| No. | Task | Challenges and Inefficiencies |
| 1 | Determine what type of data/information is needed | Who knows where all the versions and types of data regarding a specific question are stored? |
| 2 | Itemize which databases, data stores, and document repositories contain the data required | How is the complete list of systems, databases, and data stores of documents determined and maintained? Incomplete master data administration list of data sources |
| 3 | Access data | Who should be asked for access to particular databases and data stores |
| 4 | Execute data query/search | Time delays in executing manual queries that could involve different system administrators or users to run the queries |
| 5 | Verify query results from each system | Spot checking is not efficient accurate or thorough;Data matching using Excel requires skills not always available |
| 6 | Merge data | Copy and paste causes mistakesNo reliable way to ensure all the data found was merged |
| 7 | Compile results into presentable format, and circulate for review | Creating a composite view takes time. Reformatting data by manually editing the composite version can easily result in dropped data |
| 8 | Re-run queries based on comments | Many manual steps may not be repeated quickly, so the timeliness of different query executions creates additional data anomalies. |
Federated search solutions all involve some common steps, which can be repeated as multiple releases or phases as the value is understood by groups and data stores:
- Deploying the search software to either a cloud hosting provider like AWS or Azure or installing it in your own private cloud or data center. This typically takes less than 1 week.
- Inventorying data sources, including both structured (databases) and unstructured (documents, PDFs, Excel spreadsheets, etc.). This typically takes less than 4 weeks, depending on the number of applications and who needs to approve access.
- Creating search index parameters for each data source, such as re-index frequency, data types to be indexed, keywords to be indexed for, etc. This typically takes less than 6 weeks, depending on the number of unique data source types.
- Configuring the user interface, or in some expert user cases, creating optimized user interfaces for improved efficiency for specific typical search types. This can take as little as 1 week or up to 8 weeks.
- Developing a deployment strategy, to explain to users what this new capability can do, how they request access, and creation and publication of how to use the new solution.
Once an organization initially launches a federated search solution, benefits are usually quickly recognized by users and their managers. Creating some in-application mechanism for receiving comments and ideas to improve greatly accelerates adoption around the organization.
Additional training materials, such as online YouTube videos, can be very impactful, especially for knowledge workers who will benefit from the more advanced features of a platform, including:
- Fuzzy search
- Concept term search
- Complex string Boolean search
- Geo-spatially aware search approaches
After the initial release or deployment of the solution, there is often an influx of requests for new user groups to be given access, and new systems and system types to be indexed. Additional data system types often include:
- More traditional high transaction volume business systems, which are often on older – but still mission-critical – architectures such as IBM mainframes.
- Newer externally facing applications such as website content management systems, that may have many departments contributing content, and thousands of web pages and supporting content
Advanced Uses for Enterprise Search and Federated Search Solutions
While a federated search solution can benefit almost every department and every user in an organization, there are some key needs and pain points that drive the organization to move ahead initially:
- Meeting regulatory records management requirements – This project to address this requirement is often viewed as purely a compliance cost, but a broader view of records management within a larger enterprise federated search project greatly changes the cost-benefit equation.
- Classifying, sanitizing, and redacting information and documents – healthcare and financial information commonly appears on a wide range of customer and citizen documents, and much of that type of information is considered legally protected by Federal and state laws. Organizations who don’t take reasonable steps to assess and then protect documents’ contents may be subject to significant financial penalties, and very expensive to settle class action lawsuits.
- Geo-spatially tagging information within an organization – Much of an organization’s documents and data is not geo-spatially categorized or tagged, but almost all of that information does have geo-spatial relevance. Unlocking the value of your existing data when making decisions that involve location is transformational for many organizations, by helping answer the “where” questions. This type of data enhancement provides a greatly enhanced, comprehensive view of spatial information. Examples include where to open a new citizen support office, which markets to run online ads, where particular operational problems are most prevalent and may be the result of personnel or operations issues, etc.
- Citizen and Consumer Data Transparency – Government and commercial organizations have some level of data transparency requirements. Historically, organizations dealt with this using manual data access or reporting requests, including FOIA-type requests. Now, organizations are finding the manual compliance costs and risks too prohibitive, and enterprise search and federated search solutions can greatly reduce the costs and risks of manual processes.
We have helped many types of organizations achieve information awareness with our Knowvation federated search product, including Federal citizen serving agencies, intelligence agencies, military agencies, state and local archives and land records organizations, museums, national legislative bodies, and commercial and for-profit organizations in health care and financial services.
In summary, federated search for an organization can be as impactful as Google has been for being the consumer: fast, broad access to a wide range of information, in a consistent interface. There can be many needs an organization has that can be the driving catalyst for an initial federated search implementation, from responsiveness to regulatory to internal efficiency. Leading search software companies like Knowvation can help you find the support internally, develop the budget and implementation path, and ensure you help your organization move to the next level in information awareness.
If you’d like to read more in-depth articles regarding enterprise and federated search, you may enjoy these articles:
Leave a Reply